Commerce is evolving with the widespread adoption of mobile computing and with the ever increasing productivity brought on by the Internet and internet of things. The goal in commerce is for businesses to provide customers a premium/personal/efficient experience. Conventionally, there are numerous techniques to evaluate customer experience after the fact, i.e., not in real-time. For example, numerous techniques exist for after the fact capturing of transaction-related information (e.g., consumer loyalty programs, email enrollment, Enterprise resource planning (ERP), etc.). Other techniques exist for after the fact capturing of user experience (e.g., social media, Customer relationship management (CRM), etc.). Real-time data collection is limited and typically confined to systems like point-of-sale (POS) or payment gateways or in-house/3rd party software information related to a single transaction or a single customer. Further, this information is confined to a person who pays or who is subject of the transaction and may not capture data related to others involved in the experience. The current model of experience used is missing the rich context of an experience that includes all customers, all employees of the businesses involved in that particular experience, the products/service association with each customer/employee in the experience, and other related information that directly affects the customer's end-to-end experience. The current situation is limited to disconnected systems, manual workflows, and no integration of customer experience leading to an after the fact management system with manual process correction. This is complex to manage, leads to revenue leakage, is costly, and does not alleviate poor experiences.
Conventional state of the art for improving customer experience can be categorized in two approaches—i) manual processes and ii) mining transaction and social data. Manual processes can help businesses staff to support streamlining/personalization, situation/customer handling, upselling/promotion, etc. However, these process are error prone, inconsistent due to dependency on the staffs skill, do not work on high traffic days, and do not scale from one location to location. Also, there is no real-time feedback to management to intervene in real-time if necessary. Mining transaction data and social data can be employed by business software and/or third party software vendors to help businesses get some sense of how things related to customer experience can be improved. However, the information that is acted upon, does not capture the entire experience. For example, in the case of restaurant, only the person who paid for the visit has his/her data captured. In the case of a hospital visit, the data does not include a patient's attendant's data or the data of attending nurses/junior data when they visited the patient. Also, not all customers complain on social media or give feedback to the business. Plus, the data is being analyzed post the experience so it has no value to someone who could intervene on a current experience that is going badly.
It would be advantageous for businesses and consumers to have real-time customer experience management systems and methods to ensure premium/personal/efficient experiences.